Analyzing Iranian Farmers' Behavioral Intention towards Acceptance of Drip Irrigation Using Extended Technology Acceptance Model

The present study aimed to analyze sugar beet farmers’ intention towards the acceptance of drip irrigation based on an extended version of Technology Acceptance Model (TAM). The main objectives of this study were introduction of the existing acceptance behavior models, comparison of these theories with a critical point of view, presentation of a theoretical framework based on TAM, and testing the possible relationships among variables. This descriptive-correlational research was conducted through a cross-sectional survey. The statistical population of the study was sugar beet growers of Miandoab District, Iran, of which ۳۴۶ farmers were selected as the sample of the study using a multi-stage stratified random sampling method (N= ۳۳۲۶). The research instrument was a structured questionnaire, whose face, convergent, and discriminant validity were confirmed. Cronbach's alpha and composite reliability coefficients were employed to examine the reliability of research tool (۰.۷۴< α< ۰.۹۳). The results revealed that the variables of attitude, perceived ease of use, and perceived usefulness have significant positive effects on behavioral intention towards accepting drip irrigation technology. Innovation features also have an indirect effect on behavioral intention. Furthermore, the results demonstrated that independent variables of extended version of TAM could account for ۵۹.۳% of variance of behavioral intention towards drip irrigation acceptance. The significant effect of attitude towards acceptance of drip irrigation in explaining farmers' intention towards acceptance of drip irrigation technologies implies that reinforcing farmers' attitudes will increase the likelihood of activating behavioral intention towards these new irrigation methods. In general, the results of this study contribute to the development of more integrated and comprehensive models in the field of farmers' acceptance behaviors. It also provides practitioners and policy makers of agriculture and water sectors with some useful insights regarding determinants and strategies of behavioral changes.

Keywords:

Behavioral intention , Descriptive-correlational research , Innovation diffusion theory.